speechbrain.utils.hpopt module

Utilities for hyperparameter optimization. This wrapper has an optional dependency on Oríon

https://orion.readthedocs.io/en/stable/ https://github.com/Epistimio/orion

Authors
  • Artem Ploujnikov 2021

Summary

Classes:

GenericHyperparameterOptimizationReporter

A generic hyperparameter fit reporter that outputs the result as JSON to an arbitrary data stream, which may be read as a third-party tool

HyperparameterOptimizationContext

A convenience context manager that makes it possible to conditionally enable hyperparameter optimization for a recipe.

HyperparameterOptimizationReporter

A base class for hyperparameter fit reporters

OrionHyperparameterOptimizationReporter

A result reporter implementation based on Orion

Functions:

get_reporter

Attempts to get the reporter specified by the mode and reverts to a generic one if it is not available

get_trial_id

Returns the ID of the current hyperparameter optimization trial, used primarily for the name of experiment folders.

hpopt_mode

A decorator to register a reporter implementation for a hyperparameter optimization mode

hyperparameter_optimization

Initializes the hyperparameter optimization context

report_result

Reports the result using the current reporter, if available.

Reference

speechbrain.utils.hpopt.hpopt_mode(mode)[source]

A decorator to register a reporter implementation for a hyperparameter optimization mode

Parameters

mode (str) – the mode to register

Returns

f – a callable function that registers and returns the reporter class

Return type

callable

Example

>>> @hpopt_mode("raw")
... class RawHyperparameterOptimizationReporter(HyperparameterOptimizationReporter):
...    def __init__(self, *args, **kwargs):
...        super().__init__(    *args, **kwargs)
...    def report_objective(self, result):
...        objective = result[self.objective_key]
...        print(f"Objective: {objective}")
>>> reporter = get_reporter("raw", objective_key="error")
>>> result = {"error": 1.2, "train_loss": 7.2}
>>> reporter.report_objective(result)
Objective: 1.2
class speechbrain.utils.hpopt.HyperparameterOptimizationReporter(objective_key)[source]

Bases: object

A base class for hyperparameter fit reporters

Parameters

objective_key (str) – the key from the result dictionary to be used as the objective

report_objective(result)[source]

Reports the objective for hyperparameter optimization.

Parameters

result (dict) – a dictionary with the run result.

property is_available

Determines whether this reporter is available

property trial_id

The unique ID of this trial (used for folder naming)

class speechbrain.utils.hpopt.GenericHyperparameterOptimizationReporter(reference_date=None, output=None, *args, **kwargs)[source]

Bases: speechbrain.utils.hpopt.HyperparameterOptimizationReporter

A generic hyperparameter fit reporter that outputs the result as JSON to an arbitrary data stream, which may be read as a third-party tool

Parameters

objective_key (str) – the key from the result dictionary to be used as the objective

report_objective(result)[source]

Reports the objective for hyperparameter optimization.

Parameters

result (dict) – a dictionary with the run result.

Example

>>> reporter = GenericHyperparameterOptimizationReporter(
...     objective_key="error"
... )
>>> result = {"error": 1.2, "train_loss": 7.2}
>>> reporter.report_objective(result)
{"error": 1.2, "train_loss": 7.2, "objective": 1.2}
property trial_id

The unique ID of this trial (used mainly for folder naming)

Example

>>> import datetime
>>> reporter = GenericHyperparameterOptimizationReporter(
...     objective_key="error",
...     reference_date=datetime.datetime(2021, 1, 3)
... )
>>> print(reporter.trial_id)
20210103000000000000
class speechbrain.utils.hpopt.OrionHyperparameterOptimizationReporter(objective_key)[source]

Bases: speechbrain.utils.hpopt.HyperparameterOptimizationReporter

A result reporter implementation based on Orion

Parameters

orion_client (module) – the Python module for Orion

report_objective(result)[source]

Reports the objective for hyperparameter optimization.

Parameters

result (dict) – a dictionary with the run result.

property trial_id

The unique ID of this trial (used mainly for folder naming)

property is_available

Determines if Orion is available. In order for it to be available, the library needs to be installed, and at least one of ORION_EXPERIMENT_NAME, ORION_EXPERIMENT_VERSION, ORION_TRIAL_ID needs to be set

speechbrain.utils.hpopt.get_reporter(mode, *args, **kwargs)[source]

Attempts to get the reporter specified by the mode and reverts to a generic one if it is not available

Parameters

mode (str) – a string identifier for a registered hyperparametr optimization mode, corresponding to a specific reporter instance

Returns

reporter – a reporter instance

Return type

HyperparameterOptimizationReporter

Example

>>> reporter = get_reporter("generic", objective_key="error")
>>> result = {"error": 3.4, "train_loss": 1.2}
>>> reporter.report_objective(result)
{"error": 3.4, "train_loss": 1.2, "objective": 3.4}
class speechbrain.utils.hpopt.HyperparameterOptimizationContext(reporter_args=None, reporter_kwargs=None)[source]

Bases: object

A convenience context manager that makes it possible to conditionally enable hyperparameter optimization for a recipe.

Parameters
  • reporter_args (list) – arguments to the reporter class

  • reporter_kwargs (dict) – keyword arguments to the reporter class

Example

>>> ctx = HyperparameterOptimizationContext(
...     reporter_args=[],
...     reporter_kwargs={"objective_key": "error"}
... )
parse_arguments(arg_list)[source]

A version of speechbrain.parse_arguments enhanced for hyperparameter optimization.

If a parameter named ‘hpopt’ is provided, hyperparameter optimization and reporting will be enabled.

If the parameter value corresponds to a filename, it will be read as a hyperpyaml file, and the contents will be added to “overrides”. This is useful for cases where the values of certain hyperparameters are different during hyperparameter optimization vs during full training (e.g. number of epochs, saving files, etc)

Parameters

arg_list (a list of arguments) –

Returns

  • param_file (str) – The location of the parameters file.

  • run_opts (dict) – Run options, such as distributed, device, etc.

  • overrides (dict) – The overrides to pass to load_hyperpyyaml.

Example

>>> ctx = HyperparameterOptimizationContext()
>>> arg_list = ["hparams.yaml", "--x", "1", "--y", "2"]
>>> hparams_file, run_opts, overrides = ctx.parse_arguments(arg_list)
>>> print(f"File: {hparams_file}, Overrides: {overrides}")
File: hparams.yaml, Overrides: {'x': 1, 'y': 2}
speechbrain.utils.hpopt.hyperparameter_optimization(*args, **kwargs)[source]

Initializes the hyperparameter optimization context

Example

>>> import sys
>>> with hyperparameter_optimization(objective_key="error", output=sys.stdout) as hp_ctx:
...     result = {"error": 3.5, "train_loss": 2.1}
...     report_result(result)
...
{"error": 3.5, "train_loss": 2.1, "objective": 3.5}
speechbrain.utils.hpopt.report_result(result)[source]

Reports the result using the current reporter, if available. When not in hyperparameter optimization mode, this function does nothing.

Parameters

result (dict) – A dictionary of stats to be reported

Example

>>> result = {"error": 3.5, "train_loss": 2.1}
>>> report_result(result["error"])
speechbrain.utils.hpopt.get_trial_id()[source]

Returns the ID of the current hyperparameter optimization trial, used primarily for the name of experiment folders.

When using a context, the convention for identifying the trial ID will depend on the reporter being used. The default implementation returns a fixed value (“hpopt”)

Returns

trial_id – the trial identifier

Return type

str

Example

>>> trial_id = get_trial_id()
>>> trial_id
'hpopt'